SPARF View-Generalization benchmark.
In Table REF , we report the average PSNR results on the validation set of SPARF for different methods on unseen shapes during training on all 13 different object classes and on out-of-distribution views. It shows that our SuRFNet can generalize to out-of-distribution views on unseen shapes during test time, surpassing state-of-the-art PixelNeRF [1]} and VisionNerf [2]}. Visual comparisons can be found in Figure REF . As can be seen from those results, the learned 3D prior results in multi-view consistency, especially when rendering from out-of-distribution views. More results can be found in supplementary material.
<FIGURE><FIGURE>